# asia_nepa005 - Alubari - Breitenmoser Tree Ring Chronology Data #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # # Online_Resource: # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611 # # Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/3759 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa005 - Alubari - Breitenmoser Tree Ring Chronology Data #-------------------- # Investigators # Investigators: Breitenmoser, P.; Bronnimann, S.; Frank, D. #-------------------- # Description_and_Notes # Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details #-------------------- # Publication # Authors: Breitenmoser, P.; Bronnimann, S.; Frank, D. # Published_Date_or_Year: 2014-03-11 # Published_Title: Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies # Journal_Name: Climate of the Past # Volume: 10 # Edition: # Issue: # Pages: 437-449 # DOI: 10.5194/cp-10-437-2014 # Online_Resource: www.clim-past.net/10/437/2014/ # Full_Citation: # Abstract: We investigate relationships between climate and tree-ring data on a global scale using the process-based Vaganov–Shashkin Lite (VSL) forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a) to assess the VSL model performance by examining the relations between simulated and observed growth at 2287 globally distributed sites, (b) indentify optimal growth parameters found during the model calibration, and (c) to evaluate the potential of the VSL model as an observation operator for data-assimilation-based reconstructions of climate from tree-ring width. The assessment of the growth-onset threshold temperature of approximately 4–6 C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level treering series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yielded notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL model’s ability to skilfully capture the climatic signal contained in tree-ring series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate. #-------------------- # Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig # Published_Date_or_Year: 2018 # Published_Title: Additions to the last millennium reanalysis multi-proxy database # Journal_Name: Data Science Journal # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: # Online_Resource: # Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal. # Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR). The 2290 additional series include 2152 tree ring chronologies and 138 other series. They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation. A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project. The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables. Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods. #------------------ # Funding_Agency # Funding_Agency_Name: Swiss National Science Foundation # Grant: #-------------------- # Funding_Agency_Name: National Science Foundation # Grant:AGS-1304263 # Funding_Agency_Name: National Oceanic and Atmospheric Administration # Grant:NA14OAR4310176 #------------------ # Site_Information # Site_Name: Alubari # Location: # Country: Nepal # Northernmost_Latitude: 28.45 # Southernmost_Latitude: 28.45 # Easternmost_Longitude: 83.4 # Westernmost_Longitude: 83.4 # Elevation: 3000 m #-------------------- # Data_Collection # Collection_Name: asia_nepa005B # Earliest_Year: 1859 # Most_Recent_Year: 1993 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.94788453013","T2":"13.0628482339","M1":"0.0225956332174","M2":"0.548345606145"}} #-------------------- # Species # Species_Name: Himalayan pine # Species_Code: PIWA #-------------------- # Chronology: # # # #-------------------- # Variables # # Data variables follow that are preceded by ## in columns one and two. # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ##age age, , ,years AD, , , , ,N ##trsgi tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N # #-------------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: nan # age trsgi 1859 0.722 1860 0.378 1861 0.698 1862 0.962 1863 1.049 1864 1.236 1865 1.456 1866 1.263 1867 1.067 1868 1.165 1869 0.735 1870 1.074 1871 1.249 1872 1.088 1873 0.926 1874 0.391 1875 0.342 1876 0.411 1877 0.653 1878 0.979 1879 0.904 1880 1.183 1881 1.176 1882 1.157 1883 1.215 1884 0.521 1885 1.205 1886 1.417 1887 1.206 1888 1.583 1889 1.412 1890 1.797 1891 1.579 1892 1.033 1893 1.081 1894 1.28 1895 0.949 1896 0.673 1897 0.71 1898 1.018 1899 0.853 1900 0.939 1901 1.025 1902 1.366 1903 0.854 1904 1.486 1905 0.93 1906 0.846 1907 1.101 1908 0.26 1909 0.415 1910 0.358 1911 0.608 1912 0.738 1913 0.802 1914 0.816 1915 0.885 1916 0.547 1917 1.088 1918 0.741 1919 0.656 1920 0.884 1921 0.549 1922 1.025 1923 1.107 1924 1.255 1925 1.368 1926 1.26 1927 1.098 1928 1.176 1929 1.305 1930 0.887 1931 1.707 1932 1.383 1933 1.443 1934 1.596 1935 0.823 1936 1.061 1937 1.294 1938 1.468 1939 0.676 1940 0.938 1941 0.39 1942 0.903 1943 0.921 1944 1.13 1945 1.145 1946 0.973 1947 0.733 1948 0.428 1949 0.316 1950 0.603 1951 0.689 1952 1.202 1953 0.546 1954 0.818 1955 0.935 1956 1.138 1957 1.288 1958 0.651 1959 1.055 1960 0.874 1961 1.064 1962 1.321 1963 1.606 1964 1.065 1965 1.913 1966 0.341 1967 0.814 1968 0.217 1969 0.691 1970 0.976 1971 0.793 1972 1.156 1973 1.125 1974 1.424 1975 1.144 1976 1.052 1977 0.759 1978 1.002 1979 0.457 1980 0.777 1981 0.696 1982 1.181 1983 1.361 1984 1.551 1985 0.607 1986 1.58 1987 1.535 1988 1.875 1989 1.601 1990 1.191 1991 0.868 1992 0.424 1993 0.412